WWC24 - Chris Wysopal, Helmut Reisinger and Johannes Steger - Fighting Digital Threats in the Age of AI
Is your AI coding assistant creating security vulnerabilities faster than you can fix them?
#1about 3 minutes
How generative AI fundamentally changes cybersecurity threats
Generative AI increases the speed, scale, and sophistication of attacks, creating a new attack surface and requiring real-time security responses.
#2about 4 minutes
The perfection of social engineering with generative AI
AI automates and perfects social engineering attacks like phishing by improving language, tone, and scale, making them nearly undetectable.
#3about 1 minute
Moving beyond detection to preventative security measures
As AI-driven attacks become undetectable, security must shift from detection to prevention by implementing solutions like multi-factor authentication.
#4about 7 minutes
Managing security risks of AI-assisted code generation
AI-generated code is not perfect and contains vulnerabilities, requiring developers to maintain rigorous security testing and threat modeling within the development process.
#5about 1 minute
Using automated code fixing to maintain development speed
To realize the full productivity gains of AI code generation, developers need automated tools to fix the bugs and security flaws introduced by AI.
#6about 4 minutes
How AI regulation is shaping cybersecurity compliance
Regulations like the EU AI Act are necessary to manage AI risks, driving organizations toward better preparedness and establishing strict incident reporting timelines.
#7about 4 minutes
Balancing AI-driven automation with human expertise in security
While AI-powered security tools can drastically reduce remediation times, effective cybersecurity still requires a human-in-the-loop to oversee autonomous systems and improve the experience for security professionals.
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